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NMT

Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Papers

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Showing 1201–1250 of 1773 papers

TitleStatusHype
Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation—0
Memory-augmented Chinese-Uyghur Neural Machine Translation—0
Memory-augmented Neural Machine Translation—0
Memory-enhanced Decoder for Neural Machine Translation—0
Merging External Bilingual Pairs into Neural Machine Translation—0
Meta Back-translation—0
Meta Ensemble for Japanese-Chinese Neural Machine Translation: Kyoto-U+ECNU Participation to WAT 2020—0
Meta-Learning for Few-Shot NMT Adaptation—0
Meta-Learning for Low-Resource Neural Machine Translation—0
Meta-Learning for Low-Resource Neural Machine Translation—0
Mining Bilingual Word Pairs from Comparable Corpus using Apache Spark Framework—0
Mirror-Generative Neural Machine Translation—0
Mixed Multi-Head Self-Attention for Neural Machine Translation—0
Modeling Coherence for Neural Machine Translation with Dynamic and Topic Caches—0
Modeling Concentrated Cross-Attention for Neural Machine Translation with Gaussian Mixture Model—0
Modeling Discourse Structure for Document-level Neural Machine Translation—0
Modeling Future Cost for Neural Machine Translation—0
Modeling Future for Neural Machine Translation by Fusing Target Information—0
Modeling Homophone Noise for Robust Neural Machine Translation—0
Modeling Latent Sentence Structure in Neural Machine Translation—0
Modeling Multi-granularity Segmentation for Rare Words in Neural Machine Translation—0
Modeling Source Syntax for Neural Machine Translation—0
Modeling Target-Side Inflection in Neural Machine Translation—0
Modeling Task-Aware MIMO Cardinality for Efficient Multilingual Neural Machine Translation—0
Modeling Word Formation in English--German Neural Machine Translation—0
Modelling Source- and Target- Language Syntactic Information as Conditional Context in Interactive Neural Machine Translation—0
Modelling the Socialization of Creative Agents in a Master-Apprentice Setting: The Case of Movie Title Puns—0
Monolingual backtranslation in a medical speech translation system for diagnostic interviews - a NMT approach—0
Monotonic Infinite Lookback Attention for Simultaneous Machine Translation—0
Moon IME: Neural-based Chinese Pinyin Aided Input Method with Customizable Association—0
Morphological Word Embeddings for Arabic Neural Machine Translation in Low-Resource Settings—0
Morphological Word Segmentation on Agglutinative Languages for Neural Machine Translation—0
MS-UEdin Submission to the WMT2018 APE Shared Task: Dual-Source Transformer for Automatic Post-Editing—0
MTUOC: easy and free integration of NMT systems in professional translation environments—0
Much Ado About Nothing -- Identification of Zero Copulas in Hungarian Using an NMT Model—0
MUCS@Adap-MT 2020: Low Resource Domain Adaptation for Indic Machine Translation—0
MUCS@ - Machine Translation for Dravidian Languages using Stacked Long Short Term Memory—0
Multi-agent Learning for Neural Machine Translation—0
Multi-channel Encoder for Neural Machine Translation—0
Multi-Domain Neural Machine Translation—0
Multi-encoder Transformer Network for Automatic Post-Editing—0
Multi-Granularity Self-Attention for Neural Machine Translation—0
Multi-Hop Transformer for Document-Level Machine Translation—0
Multilingual Disfluency Removal using NMT—0
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters—0
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters—0
Multilingual Machine Translation Systems at WAT 2021: One-to-Many and Many-to-One Transformer based NMT—0
Multilingual Multi-Domain Adaptation Approaches for Neural Machine Translation—0
Multilingual Multi-Domain NMT for Indian Languages—0
Multilingual Multi-modal Embeddings for Natural Language Processing—0
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